Last updated 08-30-2026
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EyePop.ai
EyePop.ai lets teams train custom detection, tracking, OCR, and scene understanding models on images and video without building an ML department from scratch. You define targets, upload JPEG, PNG, or MP4 training data, and deploy trained models or pre-built Abilities through Python, Node, React SDKs, or REST APIs to the cloud, on-premise hardware, or edge devices like NVIDIA Jetson Orin and Qualcomm Snapdragon.
Where many vision vendors lock you into one deployment model, EyePop chains composable Pops so detection, pose, tracking, license plate reading, and visual intelligence run in a single on-device pass. The same Pop definition runs on GPU servers, Jetson, Snapdragon, or cloud offload without rewriting code, which matters when latency, bandwidth, or data residency rules out sending raw video upstream.
Operations teams in surveillance, broadcast, marketplaces, healthcare, agriculture, and robotics use it to turn camera feeds into structured events, searchable archives, and compliance checks instead of scrubbing timelines by hand. Self-Service Training and auto-labeling aim for hours to a working model, with many users starting from roughly 200 labeled images.
The platform won SIA Judges' Choice and Best Video Analytics at ISC West 2026. EyePop.ai is HIPAA certified and supports air-gapped on-premise deployments where video never leaves the local network.
Cloud Production includes 4,000 compute units per month with $0.05 overage billing per unit
Train custom models from JPEG, PNG, or MP4 uploads with as few as 200 labeled images
Chain composable Pops for detection, pose, OCR, tracking, and license plate reading in one pass
Deploy the same Pop definition to NVIDIA Jetson Orin, Snapdragon Dragonwing, GPU servers, or cloud
Pre-built Abilities use vision-language models like Qwen3 without a custom training cycle
On-premise setup includes a $5,000 initialization fee and roughly $1,500 hardware per edge box
Composable Pops chain detection, tracking, OCR, and scene understanding in one on-device pass.
The same Pop definition deploys across cloud, on-premise, and edge hardware without code changes.
Pre-built Abilities and Self-Service Training cover both quick starts and custom model training.
HIPAA-certified with on-premise options that keep video on the local network.
Python, Node/TypeScript, and React SDKs plus a REST API for integration.
On-premise deployments need customer-purchased hardware (roughly $1,500 per box) plus a $5,000 setup fee.
Video Agent and SB-942 compliance tools are early access and require contacting the team.
The SDK-first workflow expects developer integration rather than a purely no-code interface.
Is EyePop.ai free to try?
Yes. EyePop.ai offers a free start through dashboard.eyepop.ai so you can prototype cloud integrations before choosing a paid Cloud Production or Enterprise plan.
What does EyePop.ai cost?
EyePop.ai Cloud Production is $200 per month with 4,000 compute units included and $0.05 per extra unit. Cloud Enterprise starts at $800 per month with dedicated always-up servers and no overage fees. On-premise runtime licensing is volume-tiered per edge box.
Do I need machine learning experience to use EyePop.ai?
No dedicated ML team is required, but EyePop.ai is SDK-first for software developers. Python and Node/TypeScript SDKs, a visual Workflow Designer, and Self-Service Training with auto-labeling handle training and deployment without writing model code from scratch.
Can EyePop.ai models run on-premise or at the edge?
Yes. EyePop.ai runs the same Pop definition on NVIDIA Jetson Orin, Qualcomm Snapdragon Dragonwing, NVIDIA GPU servers, CPU-only devices, or cloud offload. On-premise video stays on the local network with only lightweight metadata transmitted.
What file formats does EyePop.ai accept for training?
EyePop.ai accepts JPEG, PNG, and MP4 files for training. For MP4 uploads, EyePop.ai extracts frames automatically for labeling and model training inside Self-Service Training.
Is customer data kept private on EyePop.ai?
Yes. EyePop.ai states it does not repurpose customer data outside authorized use cases and is HIPAA certified. Production cloud tenants are isolated, and on-premise deployments process video entirely on local hardware.
What industries does EyePop.ai serve?
EyePop.ai publishes workflows for surveillance, marketplaces, broadcast media, CDNs, construction, insurance, drones, agriculture, roofing, traffic monitoring, and healthcare. Industry pages describe specific visual intelligence tasks for each sector.